Senior Level AI Architect Jobs
Senior level ai architect jobs place experienced professionals in charge of enterprise AI strategy, platform architecture, and the cross-functional teams that build and deploy production systems at scale. Roles are concentrated across Technology & Software, Consulting & Professional Services, and Banking & Financial Services, with a mix of on-site, remote, and hybrid settings, and employers like Boston Consulting, Gusto, and Northwest Bank hiring at this level now.
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Role: Generative AI Architect
Location: Atlanta, GA – Onsite
Rate: $80/hr to $85/hr on C2C All Inclusive
Contract job
Job description:
Generative AI Architect to lead the design, architecture, and implementation of enterprise-grade AI solutions leveraging Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), and AI-driven automation platforms. The ideal candidate will have deep expertise in AI architecture, cloud-native platforms, enterprise integration, security, governance, and scalable GenAI application development. The Architect will work closely with business stakeholders, product teams, data engineers, cloud architects, and AI engineers to build innovative AI solutions that enhance customer experience, streamline insurance operations, improve knowledge management, and accelerate decision-making.
Key Responsibilities
AI & Solution Architecture
- Design end-to-end Generative AI solutions using OpenAI, Azure OpenAI, Gemini, Claude, and other enterprise LLM platforms.
- Define reference architectures, design patterns, and best practices for enterprise AI adoption.
- Architect scalable and secure AI platforms supporting conversational AI, knowledge assistants, document intelligence, and intelligent workflow automation.
- Lead architecture reviews and provide technical leadership across AI initiatives.
RAG & Knowledge Systems
- Design and implement Retrieval-Augmented Generation (RAG) architectures.
- Build enterprise knowledge retrieval solutions utilizing vector databases and semantic search technologies.
- Develop grounding strategies to reduce hallucinations and improve response accuracy.
- Integrate structured and unstructured enterprise content into AI solutions.
Agentic AI & Intelligent Automation
- Architect multi-agent systems using LangChain, LangGraph, CrewAI, AutoGen, and similar frameworks.
- Design AI workflow orchestration solutions that enable tool calling, reasoning, planning, and autonomous task execution.
- Develop intelligent automation capabilities supporting underwriting, claims processing, risk assessment, and customer service functions.
Cloud & Platform Engineering
- Design AI solutions on Azure, AWS, and/or GCP.
- Define scalable deployment architectures using Kubernetes, Docker, serverless and microservices patterns.
- Develop secure API-based AI platforms and integration frameworks.
- Collaborate with DevOps and MLOps teams to establish CI/CD pipelines and production deployment strategies.
Governance, Security & Responsible AI
- Implement Responsible AI frameworks and governance controls.
- Establish security guardrails, data protection policies, and compliance standards.
- Design authentication, authorization, secrets management, monitoring, and auditing capabilities.
- Ensure AI solutions comply with enterprise security and regulatory requirements.
Stakeholder Management
- Partner with business leaders to identify AI use cases and innovation opportunities.
- Translate business requirements into technical architecture blueprints.
- Present architecture solutions, roadmaps, and recommendations to executive stakeholders.
- Mentor engineering teams and promote AI adoption across the organization.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related field.
- Around 20 years of software architecture and enterprise solution design experience.
- 5+ years of AI/ML architecture experience.
- Hands-on experience with Generative AI and Large Language Models.
- Strong Python development experience.
- Experience designing enterprise-scale AI platforms and applications.
Required Technical Skills
Generative AI & LLMs
- OpenAI, Azure OpenAI, GPT-4o
- Gemini
- Claude
- Prompt Engineering
- Fine-Tuning
- Model Evaluation
- AI Safety & Governance
RAG & Agentic AI
- LangChain
- LangGraph
- CrewAI
- AutoGen
- RAG Architecture
- Semantic Search
- Knowledge Graphs
- Agent Orchestration
Cloud Platforms
- Microsoft Azure
- AWS
- Google Cloud Platform (GCP)
Data & Search Technologies
- Azure AI Search
- Pinecone
- FAISS
- ChromaDB
- OpenSearch
- Neo4j
- Vector Databases
Development Technologies
- Python
- FastAPI
- REST APIs
- Docker
- Kubernetes
- Terraform
- GitHub Actions
- CI/CD Pipelines
Security & Governance
- OAuth2
- RBAC
- AI Governance
- Responsible AI
- Data Privacy Controls
- Enterprise Compliance Frameworks
Preferred Experience
- Insurance industry experience (Claims, Underwriting, Risk, Policy Administration).
- AI-powered customer service or contact center solutions.
- Enterprise knowledge management implementations.
- Intelligent document processing and OCR solutions.
- Experience delivering GenAI solutions for Fortune 500 organizations.
Expected Deliverables
- Enterprise GenAI reference architecture
- AI platform design and roadmap
- AI governance framework
- Production-ready AI application architecture
- RAG and Agentic AI implementations
- Security and compliance architecture documentation
Role: Generative AI Architect
Location: Atlanta, GA – Onsite
Rate: $80/hr to $85/hr on C2C All Inclusive
Contract job
Job description:
Generative AI Architect to lead the design, architecture, and implementation of enterprise-grade AI solutions leveraging Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), and AI-driven automation platforms. The ideal candidate will have deep expertise in AI architecture, cloud-native platforms, enterprise integration, security, governance, and scalable GenAI application development. The Architect will work closely with business stakeholders, product teams, data engineers, cloud architects, and AI engineers to build innovative AI solutions that enhance customer experience, streamline insurance operations, improve knowledge management, and accelerate decision-making.
Key Responsibilities
AI & Solution Architecture
- Design end-to-end Generative AI solutions using OpenAI, Azure OpenAI, Gemini, Claude, and other enterprise LLM platforms.
- Define reference architectures, design patterns, and best practices for enterprise AI adoption.
- Architect scalable and secure AI platforms supporting conversational AI, knowledge assistants, document intelligence, and intelligent workflow automation.
- Lead architecture reviews and provide technical leadership across AI initiatives.
RAG & Knowledge Systems
- Design and implement Retrieval-Augmented Generation (RAG) architectures.
- Build enterprise knowledge retrieval solutions utilizing vector databases and semantic search technologies.
- Develop grounding strategies to reduce hallucinations and improve response accuracy.
- Integrate structured and unstructured enterprise content into AI solutions.
Agentic AI & Intelligent Automation
- Architect multi-agent systems using LangChain, LangGraph, CrewAI, AutoGen, and similar frameworks.
- Design AI workflow orchestration solutions that enable tool calling, reasoning, planning, and autonomous task execution.
- Develop intelligent automation capabilities supporting underwriting, claims processing, risk assessment, and customer service functions.
Cloud & Platform Engineering
- Design AI solutions on Azure, AWS, and/or GCP.
- Define scalable deployment architectures using Kubernetes, Docker, serverless and microservices patterns.
- Develop secure API-based AI platforms and integration frameworks.
- Collaborate with DevOps and MLOps teams to establish CI/CD pipelines and production deployment strategies.
Governance, Security & Responsible AI
- Implement Responsible AI frameworks and governance controls.
- Establish security guardrails, data protection policies, and compliance standards.
- Design authentication, authorization, secrets management, monitoring, and auditing capabilities.
- Ensure AI solutions comply with enterprise security and regulatory requirements.
Stakeholder Management
- Partner with business leaders to identify AI use cases and innovation opportunities.
- Translate business requirements into technical architecture blueprints.
- Present architecture solutions, roadmaps, and recommendations to executive stakeholders.
- Mentor engineering teams and promote AI adoption across the organization.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related field.
- Around 20 years of software architecture and enterprise solution design experience.
- 5+ years of AI/ML architecture experience.
- Hands-on experience with Generative AI and Large Language Models.
- Strong Python development experience.
- Experience designing enterprise-scale AI platforms and applications.
Required Technical Skills
Generative AI & LLMs
- OpenAI, Azure OpenAI, GPT-4o
- Gemini
- Claude
- Prompt Engineering
- Fine-Tuning
- Model Evaluation
- AI Safety & Governance
RAG & Agentic AI
- LangChain
- LangGraph
- CrewAI
- AutoGen
- RAG Architecture
- Semantic Search
- Knowledge Graphs
- Agent Orchestration
Cloud Platforms
- Microsoft Azure
- AWS
- Google Cloud Platform (GCP)
Data & Search Technologies
- Azure AI Search
- Pinecone
- FAISS
- ChromaDB
- OpenSearch
- Neo4j
- Vector Databases
Development Technologies
- Python
- FastAPI
- REST APIs
- Docker
- Kubernetes
- Terraform
- GitHub Actions
- CI/CD Pipelines
Security & Governance
- OAuth2
- RBAC
- AI Governance
- Responsible AI
- Data Privacy Controls
- Enterprise Compliance Frameworks
Preferred Experience
- Insurance industry experience (Claims, Underwriting, Risk, Policy Administration).
- AI-powered customer service or contact center solutions.
- Enterprise knowledge management implementations.
- Intelligent document processing and OCR solutions.
- Experience delivering GenAI solutions for Fortune 500 organizations.
Expected Deliverables
- Enterprise GenAI reference architecture
- AI platform design and roadmap
- AI governance framework
- Production-ready AI application architecture
- RAG and Agentic AI implementations
- Security and compliance architecture documentation
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Find JobsSenior Level AI Architect Job Market
Who's Hiring
- Boston Consulting12
- Gusto6
- Northwest Bank4
- Dell Technologies4
- Lorven Technologies4
Top Industries Hiring
- Technology & Software51
- Consulting & Professional Services16
- Banking & Financial Services9
- Fintech7
- Electronics & Hardware6
Senior Level AI Architect Jobs: Frequently Asked Questions
How do I get a senior level ai architect job?
Employers hiring at this level look for candidates who have led end-to-end AI system design, not just contributed to one. Demonstrating ownership of architecture decisions, a history of shipping production-grade models, and experience mentoring engineers or guiding technical direction sets strong candidates apart. Presenting case studies where your choices measurably improved performance, scalability, or cost puts your application ahead of peers with similar titles.
Which companies hire senior level ai architects?
Companies hiring senior level ai architects right now include Boston Consulting, Gusto, and Northwest Bank, based on current listings on Migrate Mate as of November 2026. Hiring at this level tends to come from large technology firms, financial services organizations, healthcare systems, and consulting practices that are scaling their AI infrastructure or standing up dedicated AI centers of excellence.
Are there remote senior level ai architect jobs?
Yes, though availability varies by employer and industry. About 38% of senior level ai architect openings are remote or hybrid as of November 2026, reflecting strong demand for experienced architects who can lead distributed teams. Fully on-site roles remain common in regulated industries and for positions that require close collaboration with infrastructure or hardware teams.
What makes an ai architect role senior level?
Senior level ai architect roles are defined by scope and ownership rather than task execution. Candidates are expected to set architectural direction for AI platforms, evaluate and select foundational technologies, and take accountability for system performance in production. Mentoring junior engineers, influencing cross-team roadmaps, and driving alignment between business stakeholders and technical teams are standard expectations at this stage.
Which industries hire the most senior level ai architects?
Senior level ai architect roles concentrate in Technology & Software, Consulting & Professional Services, and Banking & Financial Services, based on current listings on Migrate Mate as of November 2026. These sectors drive the highest demand because they are building or modernizing large-scale AI infrastructure, require deep expertise to govern model risk and compliance, and compete for a limited pool of professionals with proven architecture leadership experience.